Dynamic Data Fusion Analysis Method for Crack Tracking in Reinforced Concrete Based on DIC and AE

Monitoring cracks within concrete structures allows for the assessment of performance and load-bearing capacity changes, enabling early preventative measures to enhance safety and durability. This paper addresses the challenges of using Acoustic Emission (AE) technology alone to monitor full-field strain changes at crack locations by implementing a dynamic data fusion method combining Digital Image Correlation (DIC) and AE technology. This method leverages the non-contact monitoring capabilities of DIC with the energy parameter analysis and circular trajectory localization of AE to achieve data fusion on the same specimen. The method is applied during four-point bending tests on reinforced concrete beams to track crack development at various stages. The results demonstrate significant improvements in the accuracy of concrete crack detection, precise tracking of crack evolution, and detailed data analysis of crack position and size at different stages of development. This provides effective experimental support and a theoretical basis for the health monitoring and safety assurance of reinforced concrete structures.